1. Field of the Invention
The present invention relates to a method of using a video camera to automatically track a moving object of interest in the camera's field of view and, more particularly, to a method of reducing the effects of other moving objects in the field of view on the tracking of the object of interest.
2. Description of the Related Art
Video surveillance camera systems are found in many locations and may include either fixed cameras that have a fixed field of view and/or adjustable cameras that can pan, tilt and/or zoom to adjust the field of view of the camera. The video output of such cameras is typically communicated to a central location where it is displayed on one of several display screens and where security personnel may monitor the display screens for suspicious activity.
Movable cameras which may pan, tilt and/or zoom may also be used to track objects. The use of a PTZ (pan, tilt, zoom) camera system will typically reduce the number of cameras required for a given surveillance site and also thereby reduce the number and cost of the video feeds and system integration hardware such as multiplexers and switchers associated therewith. Control signals for directing the pan, tilt, zoom movements typically originate from a human operator via a joystick or from an automated video tracking system. An automated video tracking (i.e., “autotracking”) system may identify a moving object in the field of view and then track the object by moving the camera such that the moving object is maintained in the central portion of the camera's field of view.
An autotracking system may identify a moving object in the field of view by comparing several sequentially obtained images in the field of view. A change in the content of an individual pixel, or of a localized group of pixels, between sequentially obtained images may indicate the presence of a moving object that needs to be tracked. It is known for an autotracking system to create a “motion mask”, which is a pixel-by-pixel quantification of the amount, or probability, of content change in the pixels between sequentially obtained images. By identifying groupings of pixels that have had changes of content between sequentially obtained images, the system can identify a moving object within the field of view.
There have been identified several problems in relation to the use of autotracking systems. For example, the autotracking system may issue an alarm when it detects a suspicious moving object that could possibly be an intruder. A problem, however, is that the system may issue false alarms when it detects “static movement”, i.e., background movement, that the system interprets as a suspicious target. An example of a source of such static movement is a flag waving in the breeze. A related problem is that the presence of static movement in the field of view may cause inefficiency in tracking actual suspicious targets. Lastly, the presence of static movement in the field of view may confuse the system and cause the system to lose track of an actual suspicious target.
Although various systems have addressed the need to provide motion masks in a surveillance camera system, none have addressed the need to filter out static movement when using motion masks in an autotracking surveillance system.